Online unbalance compensation of a maglev rotor with two active magnetic bearings based on the LMS algorithm and the influence coefficient method

Zhou, Jian; Wu, Huachun; Wang, Weiyu; Yang, Kezhen; Hu, Yefa; Guo, Xinhua; Song, Chunsheng

doi:10.1016/j.ymssp.2021.108460

Cited by 16 publications

(6 citation statements)

References 18 publications

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“…There is a fixed phase difference between the rotor phase and the imbalance phase of the rotor in equation ( 4). The utilization of the rising edge of the rotational speed sensor signal as a reference phase enhances the effectiveness and reliability of the VPAC algorithm in both steady-state and time-varying speed operating conditions [36].…”

Section: Rotor Phase Calculatormentioning

confidence: 99%

“…However, the ILC algorithm may amplify the noise and disturbances with low frequency. Some researchers implement the unbalance control of the AMB system using the adaptive filtering technique [34][35][36]. Shi et al designed an adaptive feed-forward vibration controller based on least mean squares (LMSs) to realize both displacement-nulling and current-nulling for the AMB system [34].…”

Section: Introductionmentioning

confidence: 99%

“…However, the convergence time of these two approaches is relatively long. Jian et al [36] employed the LMS algorithm to determine the vibration signal phase before calculating the compensation signal using the influence coefficient method. However, this approach has a complicated procedure, and it is unsuitable for applications with time-varying rotational speeds.…”

Section: Introductionmentioning

confidence: 99%

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Synchronous disturbance suppression of active magnetic bearing rotor systems using variable period adaptive control algorithm

Bian,

Shi,

Sun

et al. 2023

Meas. Sci. Technol.

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This paper aims to investigate the issue of suppressing synchronous vibration in active magnetic bearing (AMB) systems. The rotor mass imbalance is a challenging problem for the AMB system, which will cause synchronous vibration and severely aﬀect the system stability and safety. However, existing algorithms based on the iterative feed-forward control strategy ﬁnd it diﬃcult to simultaneously ensure system’s stability and competent convergence performance. They struggle to maintain tolerable robustness within the system operating bandwidth. This paper proposes a variable period adaptive control algorithm to address these challenges. The overall control scheme can achieve current and displacement elimination separately by switching control structures and is applicable to variable speed conditions. This algorithm can adaptively adjust the iteration period based on rotational speed to ensure both splendid convergence performance and system dynamic performance. Furthermore, this work employs the Lyapunov method to analyze the algorithm’s asymptotic stability and provides a lookup table for algorithm parameters. This could signiﬁcantly enhance the robustness and stability of the algorithm within the system operating bandwidth. Finally, this methodology has proven to be eﬀective and superior in simulations and experiments.

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Section: Rotor Phase Calculatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Synchronous disturbance suppression of active magnetic bearing rotor systems using variable period adaptive control algorithm

Bian,

Shi,

Sun

et al. 2023

Meas. Sci. Technol.

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show abstract

“…The deviation between the machine and the foundation installation mainly refers to the deviation of the connection stiffness between the machine and the foundation, and the deviation of the machine installation levelness. These assembly errors will lead to the inconsistency between the inertial axis and the rotational axis, so the unbalanced mass will change to some extent [25] .…”

Section: Unbalance Variation After Assemblymentioning

confidence: 99%

Unbalanced variation after assembly and double-speed influence coefficient method in the threshing drum

Yu,

Li,

et al. 2023

International Journal of Agricultural and Biological Engineering

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Though the component of threshing drum is pre-balancing on the factory, the drum after assembly still has the problem of unbalanced vibration. In this study, the unbalance mechanism produced by assembly were introduced and the centroid propagation model in the series rotation system was established. The influence of the eccentricity and assembly phase on the assembly unbalance was studied. It is shown that there was a superposition effect between the initial centroid eccentricity caused by the machining error and the centroid eccentricity caused by assembly error, the unbalance amount under the in-phase assembly was larger than that of the anti-phase assembly. Moreover, the unbalance variation was experimentally investigated using in-field balancing detection on the test rig and combine harvester. The experiment results showed the excellent vibration reduction effect of in-field balancing, which showed a reduction of 83.0% and 85.8%. In order to increase the range of in-field balance detection and reduce the calculation error, the double-speed influence coefficient method was proposed. The proposed method adopted the way of first low-speed pre-balancing, and then high-speed precision balance, taking advantage of vibration information at two speeds and avoids nonlinear vibration conditions caused by high unbalanced vibration. Finally, the double-speed influence coefficient method was verified on the test rig. The vibration reduction effect of proposed method was better than the traditional method.

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“…The control principle of the AMB-rotor system is as follows: the displacement sensor detects the rotor position in real time and feeds it back to the controller. The controller outputs the control signal according to the feedback signal and amplifies the signal through the power amplifier to output the control current to the magnetic bearing, thus generating electromagnetic force to make the stable rotor suspension (Zhou et al, 2022). Therefore, the accuracy of rotor suspension largely depends on the detection accuracy of the sensor.…”

Section: Introductionmentioning

confidence: 99%

Influence of displacement sensor runout on active magnetic bearing-rotor system and control analysis

Jian

Cheng

2023

Journal of Vibration and Control

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In the active magnetic bearing (AMB)-rotor system, a displacement sensor is one of the indispensable components. It detects the displacement of the rotor in real time and feeds back to the control system to realize the stable suspension of the rotor. However, due to electromagnetic interference, unstable power supply, poor grounding, and uneven rotor surface, the signal runout of the displacement sensor can often occur, resulting in rotor vibration. Given the above problems, this paper establishes the control model of the AMB-rotor system, lists three typical sensor runout signals, then analyzes the influence of different types of sensor runout on the system, and discusses the control methods under different sensor runout conditions. The research results have a specific guiding significance for vibration control of the maglev rotor under sensor runout influence.

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Online unbalance compensation of a maglev rotor with two active magnetic bearings based on the LMS algorithm and the influence coefficient method

Cited by 16 publications

References 18 publications

Synchronous disturbance suppression of active magnetic bearing rotor systems using variable period adaptive control algorithm

Synchronous disturbance suppression of active magnetic bearing rotor systems using variable period adaptive control algorithm

Unbalanced variation after assembly and double-speed influence coefficient method in the threshing drum

Influence of displacement sensor runout on active magnetic bearing-rotor system and control analysis

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